논문 초록

Information fusion of heterogeneous sensors for enriched personal healthcare activity logging
Despite the proliferation of wearable devices and mobile apps for healthcare activity monitoring, no model that complementarily integrates these monitoring logs making up personal big data has been put forth. In addition, such datasets are too large to yield meaningful information. To deal with data from heterogeneous sources, a common format and information fusion model for the complementary aggregation and abstraction of logs are necessary. We introduce a sensor and activity model that classifies heterogeneous sensors and propose an information fusion method that reorganises personal healthcare activity logs and visualises them hierarchically in a harmonised way while providing a meaningful summary.
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